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BitMEX CEO Becomes the Voice of Reason Amid the AI Boom

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BitMEX
News

BitMEX CEO Becomes the Voice of Reason Amid the AI Boom

BitMEX CEO Becomes the Voice of Reason Amid the AI Boom

There is a clamor and hype surrounding AI. The speed at which the tech is developing has raised some ethical concerns. Among this voice, the CEO of Bitmix has a different opinion.

There has been a single way tech buildout rolls out:

Tech Rollout Overbuilds ➔ Market Crash / Failures ➔ Government Bailout (Money Printing) ➔ Currency Devaluation ➔ Capital Flees to Crypto

As per Arthur Hayes’ recent statement, this is how investment in AI infra will actually end. This seems like the most probable scenario.

In recent days, conversations around AI have taken a cautious turn- from photo-ops with the President to a new label, “superintelligence.” This marketing play has made the masses fairly aware, and more skeptical, of AI’s actual growth than ever before.

But there’s not much that can be done when those with the power to make the move want to see it through as the first of its kind, the most innovative breakthrough in any field. This is alongside the various “performative” warnings (accompanied by nods) and the need for regulations delegated by the AI Avengers- from Musk to Amodei.

And if that wasn’t any simpler- Huang disagreed with the need for regulations on AI models, and Sam Altman basically told the world to ‘suck it up’: what are a few grievances in the face of innovation? Imagine superintelligence.

However, the BitMEX CEO might be on the right side of the fence. He believes humanity (the tech bros) investing trillions of dollars into AI data centers is a sheer waste of time. The massive data center buildout is going nowhere, and as with any other tech rollout (such as the 19th-century railways or the 1990s Dot-Com fiber-optic buildout), it will end in an asset crash.

With AI infra being built at such a scale, wouldn’t computing power become cheap and accessible? It might; that’s the unsure part. But the pressure point is that these AI and tech companies are burning cash- without matching bottom-line impact.

Is overbuilding infrastructure the right thing to do when it’s leading to bailouts but not profit?

This creates a setback. And that has been the problem with AI.

The tech itself (aside from generative AI) hasn’t been a bottleneck. There are fields where AI’s potential is quite evident. It’s the over-investment, the promises, and the over-hyping that’s worrying skeptics.

“Once the data centers currently under construction are completed, infrastructure providers will seek payment for the compute those companies have committed to,” emphasizes Arthur Hayes.

Open AI
News

OpenAI Follows in Anthropic’s Footsteps; Adds Text-Watermarking to ChatGPT and Codex

OpenAI Follows in Anthropic’s Footsteps; Adds Text-Watermarking to ChatGPT and Codex

Text-watermarking is now added to ChatGPT after Claude. Who is really benefiting from it?

A couple of weeks ago, Anthropic announced that Claude-generated texts will now have invisible watermarks, which caused quite an uproar. Meant to label synthetic content and for professors and teachers to track AI usage across assignments, the response to watermarking was divided. And it still is.

OpenAI is following through on that, even though it’s mostly to abide by the EU’s AI Act.

ChatGPT and Codex will now possess OpenAI’s text watermarking technology, textGrain. This will add invisible, machine-readable watermarking to the generated content/texts.

According to the announcement made by OpenAI, this isn’t the global default and is merely applicable to users based within the EU.

Some part of the market was hopeful. Readers and platforms should know when content is AI-generated, right? For transparency and ownership. Owing to this, even Substack now has Pangram added to its platform for users to gauge if a piece or any part of it is AI-generated.

But the benefits aren’t entirely limited to users. There’s another angle to the reformation: help identify recursive content for future AI models and filter out low-quality recurrent information.

Much of the conversation around AI-generated text has boiled down to its quality. AI companies had an idea- let’s focus on feeding AI only high-quality content. Not AI content fed back into AI models.

Now there’s the other side of the market, which isn’t happy.

Their reigning concern is: what if human work (that’s merely proofread or edited slightly by AI) is also marked as AI-generated?

These watermarks aren’t a measure of accuracy or ownership, and neither do they indicate how much of the content is truly human. There’s no variable to truly differentiate. And if wrong, can lead to unfair penalization.

OpenAI’s only advice for now? Publishing a disclaimer.

Sap
News

SAP Buys TechWolf: Does Enterprise HR Finally Care About Real Skills?

SAP Buys TechWolf: Does Enterprise HR Finally Care About Real Skills?

SAP is buying TechWolf to bring AI-powered skills mapping to SuccessFactors. Here is why tracking actual work capabilities changes enterprise HR forever.

SAP just agreed to acquire TechWolf, a Ghent-based AI startup that maps employee skills and daily work. The enterprise tech giant plans to integrate TechWolf’s work-intelligence engine directly into its flagship SuccessFactors HR platform.

Most corporate HR databases rely on outdated resumes, self-reported skills, and annual reviews that turn stale within months.

TechWolf flips that dynamic on its head.

Instead of asking employees what they can do, its AI analyzes daily project records, workflows, and output to build a live map of workforce capabilities. Enterprise leaders suddenly gain clear visibility into who possesses critical skills and where automation creates skill gaps.

As companies scramble to restructure their organizations around generative AI, this real-time data becomes indispensable.

This deal proves that traditional job titles no longer reflect modern corporate work. TechWolf’s evidence-based tracking replaces corporate guessing games with actual data, giving SAP a massive edge over competitors like Workday and Oracle.

SAP’s move signals a fundamental shift in corporate strategy.

Companies can no longer manage talent through rigid, static organizational charts while spending millions on blind restructuring. Enterprise HR software must show what workforce talent actually accomplishes in real time.

Static job descriptions died long ago, and SAP just bought the system that replaces them.

Anthropic
News

Anthropic’s CEO Sits “Middle of the Pack” at $18 Million

Anthropic’s CEO Sits “Middle of the Pack” at $18 Million

Anthropic CEO Dario Amodei earned $18 million ahead of a $2 trillion IPO.

Anthropic CEO Dario Amodei earned $18 million last year, placing him squarely in the middle of Big Tech’s executive pay scale.

According to Anthropic’s latest IPO filing, Amodei’s total earnings sit right around the industry median.

S&P 500 tech leaders routinely clear over $22 million, and extreme outliers snag hundreds of millions in stock options. On paper, Amodei makes more than the reported base pay of Alphabet’s Sundar Pichai or Amazon’s Andy Jassy, yet lags behind mega-earners at Oracle and NVIDIA.

However, focusing on that $18 million annual figure completely misses the real story.

Founder-CEOs do not rely on yearly pay packages to build generational wealth.

Anthropic plans an upcoming public debut targeting a massive $2 trillion valuation. Amodei and his six co-founders hold equity stakes that could soon translate into tens of billions of dollars. Annual salaries and performance bonuses serve as mere pocket change compared to early equity in a booming AI firm.

Even with the siblings pledging 80% of their personal shares to philanthropic causes, Amodei’s wealth trajectory remains staggering. Mid-pack CEO salaries are akin to accounting smoke screens for tech founders.

Google
News

Google Hits Pause on its Bug Bounty Program Because of AI Slop

Google Hits Pause on its Bug Bounty Program Because of AI Slop

Google froze its open-source bug bounty program due to a flood of AI-generated slop. Is the future of tech automated security?

Google hit the brakes on its Open Source Software Vulnerability Rewards Program, and AI spam is to blame.

Script kiddies and hopeful bounty hunters leverage LLMs to churn out automated vulnerability reports. But these bots throw nonsense at human maintainers instead of finding real security flaws. Hallucinated code, bogus exploits, and endless noise completely overwhelm Google’s engineering teams. And manually triaging thousands of junk filings drains time that engineers should spend fixing code. Consequently, Google slammed the brakes on October 1, promising an update in early 2027.

This freeze exposes a major flaw in current AI tools. Generative AI excels at pattern matching, but completely fails at actual reasoning. Security research requires deep context and real validation- things a prompt cannot replicate. When novice hackers treat AI as a free money printer, tech companies pay the price in lost engineering hours.

Google’s decision sets a vital precedent.

Tech platforms cannot allow automated slop to destroy crucial crowdsourced security. The only solution? Bug bounty platforms must build strict AI filters or impose penalties for garbage submissions. Or the alternate scenario? Genuine security researchers will keep losing space to automated noise.

AI can generate code instantly, but humans still need to clean up the mess.

Superintelligence
News

Tech Giants Shake Hands on a Non-Binding Contract While Posing for “Superintelligence” Photo-Ops

Tech Giants Shake Hands on a Non-Binding Contract While Posing for “Superintelligence” Photo-Ops

Swapping labels and signing honor-system pledges isn’t going to protect society from high-stakes AI risks. But are tech leaders aware?

AI to superintelligence has been an awry path, full of uncertainties and hidden risks that have instilled doubts in an optimistic audience of techies, investors, and tech leaders.

Will it or won’t it is the question users are now asking of AI. And the answer has been scattered in all directions. Recently, AI leaders from Musk to Amodei to Altman flagged the need for regulations and stringent governance practices around the tech, which Huang thought wasn’t the need of the hour.

But then Altman has now gone on to assert that AI falling short of delivering the desired outcomes is merely a stepping stone for what’s to come- and that is superintelligence.

AI, according to them, is only meant to be the foundation. The real goal, as they’ve been telling the crowd, is superintelligence (or that’s what they’re calling it).

The rebranding effort around AI is at full power- so much so that even Trump has now pivoted to calling the tech by its new name. The event that followed?

Tech leaders and policymakers recently gathered at the White House to unveil the “White House Accord on Super Intelligence”, rebranding advanced AI under a shiny new label while getting major tech CEOs to sign a joint safety commitment.

But can fancy new terminology and a handshake agreement fix AI’s growing PR problem?

At the surface level, it all seems like photo-ops and a marketing play to basically relay that – “AI has killer (and killing potential), but superintelligence doesn’t- and that’s our real goal.”

Here’s the catch: the accord is completely non-binding. It relies on voluntary promises from tech giants rather than enforceable government regulations.